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Section 1.7 Data Science

Data Science is a new, and rapidly growing interdisciplinary field of study. It focuses on using a combination of computation and mathematics to answer questions and solve problems using large amounts of data.
A data scientist will be responsible for gathering data and then using it to find trends, make forecasts, and communicate information. To do this, they will write computer programs, apply various mathematical techniques from statistics, calculus, and linear algebra, and make use of advanced tools like machine learning algorithms.
Although there is a general set of skills used by all data scientists, an individual data scientist often focuses on a particular domain. They may specialize in working with data from biological sciences, business and marketing, sports management, geology, or any other domain where large amounts of data exist. To effectively work in one of these domains, a data scientist often needs field-specific knowledge in addition to their general data science skills.
Figure 1.7.1. Data Science combines mathematics, computer science, and knowledge in a domain.

Subsection 1.7.1 Typical careers

  1. Data Scientist or Data Analyst

Subsection 1.7.2 Education

Working as a data analyst or scientist generally requires a Bachelor’s degree or graduate degree (Master’s or Ph.D.).
Because Data Science is a cross-disciplinary field, degrees in data science can be found in many different programs. Some Data Science degrees are offered by math departments, others as concentrations in a degree in computer science. Some specialized data science programs may exist in other departments - a biology department may offer a degree in “Bio Informatics” or “Biological Data Science”.
Any data science degree is probably going to feature:
  • A solid foundation in programming and algorithms.
  • Mathematics including statistics and likely calculus and linear algebra.
  • Exposure to the techniques and tools used in data science.
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